import  pandas as pd
import os
import  json
import tos
import  time
import uuid
import mysql.connector
import sys
from bytehouse_driver import Client
import logging
import numpy as np

# Access key 和 Secret key 可在用户火山引擎账号中查找
ak = "AKLTMmFmMzVmNmY5ZDEyNDNmNWEyZTU2MDM3Y2EzMDJlZTk"
sk = "WVdNeFpXRXdNekV4Tm1ZME5EZGxPRGc0TUdFNE1HWXdNV1ZqTkdNNU9HRQ=="
# your endpoint 和 your region 填写Bucket 所在区域对应的Endpoint。# 以华北2(北京)为例，your endpoint 填写 tos-cn-beijing.volces.com，your region 填写 cn-beijing。
endpoint = "tos-cn-beijing.ivolces.com"
region = "cn-beijing"

def get_dict(vechicle_id,start_time_str,bagid,path,scid_dict,level1,level2,level3):
    dict = {}
    dict["vehicle_id"] = vechicle_id
    dict["start_time_str"] = start_time_str
    dict["scid"] = bagid
    dict["path"] = path
    dict["level1"] = level1
    dict["level2"] = level2
    dict["level3"] = level3
    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
    month = start_time_str[0:4] + start_time_str[5:7]
    dict["day"] = day
    dict["month"] = month
    dict["scid_start_time_str"] = scid_dict["scid_start_time_str"]
    dict["icu2_odometer"] = scid_dict["ICU2_Odometer"]
    dict["idb3_vehiclespd"] = scid_dict["IDB3_VehicleSpd"]
    dict["acu2_longaccsensorvalue"] = scid_dict["ACU2_LongAccSensorValue"]
    dict["acu2_lataccsensorvalue"] = scid_dict["ACU2_LatAccSensorValue"]
    dict["acu2_vehicledynyawrate"] = scid_dict["ACU2_VehicleDynYawRate"]
    dict["eps1_steeranglespd"] = scid_dict["EPS1_SteerAngleSpd"]
    dict["lane_curvature"] = scid_dict["lane_curvature"]
    dict["eps1_torsionbartorque"] = scid_dict["EPS1_TorsionBarTorque"]
    dict["cs1_gearpositionreqst"] = scid_dict["CS1_GearPositionReqSt"]
    dict["lane_curvature"] = scid_dict["lane_curvature"]

    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
    dict["uid"] = uid
    return dict
def add_to_bytehouse_dict(dict):
    HOST="bytehouse-cn-beijing.volces.com"
    PORT="19000"
    API_KEY="q2p9nLj7tq:TKOCmgrMKp"
    # 配置数据库连接信息
    DATABASE="dwd"
    client = Client.from_url('bytehouse://{}:{}/?user=bytehouse&password={}&database={}&secure=true'.format(HOST, PORT, API_KEY, DATABASE))
    start_time_str=dict['scid_start_time_str']
    hour = start_time_str[11:13]

    client.execute("INSERT INTO dwd.dwd_trigger_sc_ep40_tda4_v5 VALUES", [
        [dict['vehicle_id'], dict['start_time_str'], dict['scid'], dict['path'], dict['level1'], dict['level2'],
         dict['level3'], dict['day'], dict['month'],dict["scid_start_time_str"], dict['icu2_odometer'], dict['idb3_vehiclespd'],
         dict['acu2_longaccsensorvalue'], dict['acu2_lataccsensorvalue'], dict['acu2_vehicledynyawrate'],
         dict['eps1_steeranglespd'],dict["lane_curvature"],dict['eps1_torsionbartorque'], dict['cs1_gearpositionreqst'], dict['uid'],dict['day']]])
def get_dict_list(dict):
    data_list=[]
    data_list.append(dict['vehicle_id'])
    data_list.append(dict['start_time_str'])
    data_list.append(dict['scid'])
    data_list.append(dict['path'])
    data_list.append(dict['level1'])
    data_list.append(dict['level2'])
    data_list.append(dict['level3'])
    data_list.append(dict['day'])
    data_list.append(dict['month'])
    data_list.append(dict["scid_start_time_str"])
    data_list.append(dict['icu2_odometer'])
    data_list.append(dict['idb3_vehiclespd'])
    data_list.append(dict['acu2_longaccsensorvalue'])
    data_list.append(dict['acu2_lataccsensorvalue'])
    data_list.append(dict['acu2_vehicledynyawrate'])
    data_list.append(dict['eps1_steeranglespd'])
    data_list.append(dict['lane_curvature'])
    data_list.append(dict['eps1_torsionbartorque'])
    data_list.append(dict['cs1_gearpositionreqst'])
    data_list.append(dict['uid'])
    data_list.append(dict['day'])
    return data_list
def add_to_bytehouse(dict_list):

    print(dict_list)
    HOST="bytehouse-cn-beijing.volces.com"
    PORT="19000"
    API_KEY="q2p9nLj7tq:TKOCmgrMKp"
    # 配置数据库连接信息
    DATABASE="dwd"
    client = Client.from_url('bytehouse://{}:{}/?user=bytehouse&password={}&database={}&secure=true'.format(HOST, PORT, API_KEY, DATABASE))
    client.execute("INSERT INTO dwd.dwd_trigger_sc_ep40_tda4_v5 VALUES", dict_list)
def get_scid_time(df_nnp_can_out,df_nnp_can_100ms):
    df_nnp_can100ms_list= df_nnp_can_100ms[
        ['start_time_str','path','nsecs','VLCCDHypotheses_Hypothesis_0_fTTC','VLCCDHypotheses_Hypothesis_0_fDistX','VLCCDHypotheses_Hypothesis_0_fDistY',
         'VLCCDHypotheses_Hypothesis_0_fVrelX','VLCCDHypotheses_Hypothesis_0_fVrelY','IDB3_VehicleSpd','ACU2_LongAccSensorValue','ACU2_LatAccSensorValue',
         'ACU2_VehicleDynYawRate','IDB1_BrakePedalApplied','EPS1_SteerAngleSpd','CamLaneData_CourseInfo_1_CourseInfoSegNear_f_C0',
         'ICU2_Odometer','EPS1_TorsionBarTorque','CS1_GearPositionReqSt'
         ]].values.tolist()

    df_nnp_canout_list= df_nnp_can_out[
        ['start_time_str','path','nsecs','ADCS8_NNPSysState','ADCS12_NNP_State_Reminder','ADCS12_P2N_State_Reminder'
         ]].values.tolist()


    found_index = -9999
    found_start_time_str=""
    found_nsecs=0

    # 遍历列表
    ADCS8_NNPSysState_last=df_nnp_canout_list[0][3]
    for index, element in enumerate(df_nnp_canout_list):
        start_time_str=element[0]
        path = element[1]
        nsecs = element[2]
        ADCS8_NNPSysState = element[3]
        ADCS12_NNP_State_Reminder = element[4]
        ADCS12_P2N_State_Reminder = element[5]
        if (ADCS8_NNPSysState_last==1 and ADCS8_NNPSysState==2) or (ADCS12_NNP_State_Reminder==2) or (ADCS12_NNP_State_Reminder==7) or (ADCS12_P2N_State_Reminder==7):
            found_index = index
            found_nsecs=nsecs
            found_start_time_str=start_time_str
            break  # 找到第一个符合条件的元素就跳出循环
        ADCS8_NNPSysState_last=ADCS8_NNPSysState
    logging.info("found_index: "+str(found_index))
    logging.info("found_nsecs: " + str(found_nsecs))

    list_data=get_can_out_100ms_list(df_nnp_can100ms_list, found_nsecs,found_start_time_str)
    dict_scid = {}
    if list_data is not None and len(list_data) > 0:
        ICU2_Odometer = list_data[15]
        IDB3_VehicleSpd = list_data[8]
        ACU2_LongAccSensorValue = list_data[9]
        ACU2_LatAccSensorValue = list_data[10]
        ACU2_VehicleDynYawRate = list_data[11]
        EPS1_SteerAngleSpd = list_data[13]
        lane_curvature = list_data[14]
        EPS1_TorsionBarTorque = list_data[16]
        CS1_GearPositionReqSt = list_data[17]
        dict_scid["scid_start_time_str"] = found_start_time_str
        dict_scid["ICU2_Odometer"] = ICU2_Odometer
        dict_scid["IDB3_VehicleSpd"] = IDB3_VehicleSpd
        dict_scid["ACU2_LongAccSensorValue"] = ACU2_LongAccSensorValue
        dict_scid["ACU2_LatAccSensorValue"] = ACU2_LatAccSensorValue
        dict_scid["ACU2_VehicleDynYawRate"] = ACU2_VehicleDynYawRate
        dict_scid["EPS1_SteerAngleSpd"] = EPS1_SteerAngleSpd
        dict_scid["lane_curvature"] = lane_curvature
        dict_scid["EPS1_TorsionBarTorque"] = EPS1_TorsionBarTorque
        dict_scid["CS1_GearPositionReqSt"] = CS1_GearPositionReqSt
    else:
        dict_scid["scid_start_time_str"] = df_nnp_can100ms_list[0][0]
        dict_scid["ICU2_Odometer"] = None
        dict_scid["IDB3_VehicleSpd"] = None
        dict_scid["ACU2_LongAccSensorValue"] = None
        dict_scid["ACU2_LatAccSensorValue"] = None
        dict_scid["ACU2_VehicleDynYawRate"] = None
        dict_scid["EPS1_SteerAngleSpd"] = None
        dict_scid["lane_curvature"] = None
        dict_scid["EPS1_TorsionBarTorque"] = None
        dict_scid["CS1_GearPositionReqSt"] = None




    return dict_scid
def get_model_feature(found_index,df_list,start_time_str):
    if found_index >= 11:
        VLCCDHypotheses_Hypothesis_0_fTTC_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fTTC_last= [row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_last_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_last)
        AEB_Target_Estimated_Time_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fTTC_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fTTC_next =[row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_next_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_next)
        AEB_Target_Estimated_Time_post = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistX_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistX_last= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_last)
        AEB_Target_Longitudinal_Distance_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp)


        VLCCDHypotheses_Hypothesis_0_fDistX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistX_next= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_next)
        AEB_Target_Longitudinal_Distance_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistY_last = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_last)
        AEB_Target_Cross_Range_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistY_next = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_next)
        AEB_Target_Cross_Range_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_last)
        AEB_Target_Longitudinal_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_next)
        AEB_Target_Longitudinal_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_last_list = df_list[found_index - 11:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_last)
        AEB_Target_Lateral_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_next)
        AEB_Target_Lateral_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp)

        IDB3_VehicleSpd_last_list = df_list[found_index - 11:found_index - 1]
        IDB3_VehicleSpd_last = [row[8] for row in IDB3_VehicleSpd_last_list]
        IDB3_VehicleSpd_last_nnp = np.array(IDB3_VehicleSpd_last)
        IDB3_VehicleSpd_pre = np.mean(IDB3_VehicleSpd_last_nnp)

        IDB3_VehicleSpd_last_next_list = df_list[found_index + 1:found_index + 11]
        IDB3_VehicleSpd_last_next = [row[8] for row in IDB3_VehicleSpd_last_next_list]
        IDB3_VehicleSpd_last_next_nnp = np.array(IDB3_VehicleSpd_last_next)
        IDB3_VehicleSpd_post = np.mean(IDB3_VehicleSpd_last_next_nnp)

        ACU2_LongAccSensorValue_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_LongAccSensorValue_last = [row[9] for row in ACU2_LongAccSensorValue_last_list]
        ACU2_LongAccSensorValue_last_nnp = np.array(ACU2_LongAccSensorValue_last)
        ACU2_LongAccSensorValue_pre = np.mean(ACU2_LongAccSensorValue_last_nnp)

        ACU2_LongAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LongAccSensorValue_next = [row[9] for row in ACU2_LongAccSensorValue_next_list]
        ACU2_LongAccSensorValue_next_nnp = np.array(ACU2_LongAccSensorValue_next)
        ACU2_LongAccSensorValue_post = np.mean(ACU2_LongAccSensorValue_next_nnp)

        ACU2_LatAccSensorValue_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_LatAccSensorValue_last = [row[10] for row in ACU2_LatAccSensorValue_last_list]
        ACU2_LatAccSensorValue_last_nnp = np.array(ACU2_LatAccSensorValue_last)
        ACU2_LatAccSensorValue_pre = np.mean(ACU2_LatAccSensorValue_last_nnp)

        ACU2_LatAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LatAccSensorValue_next = [row[10] for row in ACU2_LatAccSensorValue_next_list]
        ACU2_LatAccSensorValue_next_nnp = np.array(ACU2_LatAccSensorValue_next)
        ACU2_LatAccSensorValue_post = np.mean(ACU2_LatAccSensorValue_next_nnp)

        ACU2_VehicleDynYawRate_last_list = df_list[found_index - 11:found_index - 1]
        ACU2_VehicleDynYawRate_last = [row[11] for row in ACU2_VehicleDynYawRate_last_list]
        ACU2_VehicleDynYawRate_last_nnp = np.array(ACU2_VehicleDynYawRate_last)
        ACU2_VehicleDynYawRate_pre = np.mean(ACU2_VehicleDynYawRate_last_nnp)

        ACU2_VehicleDynYawRate_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_VehicleDynYawRate_next = [row[11] for row in ACU2_VehicleDynYawRate_next_list]
        ACU2_VehicleDynYawRate_next_nnp = np.array(ACU2_VehicleDynYawRate_next)
        ACU2_VehicleDynYawRate_post = np.mean(ACU2_VehicleDynYawRate_next_nnp)

        AEB_Target_Estimated_Time_diff = AEB_Target_Estimated_Time_post - AEB_Target_Estimated_Time_pre
        AEB_Target_Longitudinal_Distance_diff = AEB_Target_Longitudinal_Distance_post - AEB_Target_Longitudinal_Distance_pre
        AEB_Target_Cross_Range_diff = AEB_Target_Cross_Range_post - AEB_Target_Cross_Range_pre
        AEB_Target_Longitudinal_Velocity_diff = AEB_Target_Longitudinal_Velocity_post - AEB_Target_Longitudinal_Velocity_pre
        AEB_Target_Lateral_Velocity_diff = AEB_Target_Lateral_Velocity_post - AEB_Target_Lateral_Velocity_pre
        IDB3_VehicleSpd_diff = IDB3_VehicleSpd_post - IDB3_VehicleSpd_pre
        ACU2_LongAccSensorValue_diff = ACU2_LongAccSensorValue_post - ACU2_LongAccSensorValue_pre
        ACU2_LatAccSensorValue_diff = ACU2_LatAccSensorValue_post - ACU2_LatAccSensorValue_pre
        ACU2_VehicleDynYawRate_diff = ACU2_VehicleDynYawRate_post - ACU2_VehicleDynYawRate_pre

        IDB1_BrakePedalApplied_next_list = df_list[found_index + 1:found_index + 11]
        IDB1_BrakePedalApplied_next = [row[12] for row in IDB1_BrakePedalApplied_next_list]
        IDB1_BrakePedalApplied_next_nnp = np.array(IDB1_BrakePedalApplied_next)
        IDB1_BrakePedalApplied = np.mean(IDB1_BrakePedalApplied_next_nnp)

        EPS1_SteerAngleSpd_next_list = df_list[found_index + 1:found_index + 11]
        EPS1_SteerAngleSpd_next = [row[13] for row in EPS1_SteerAngleSpd_next_list]
        EPS1_SteerAngleSpd_next_nnp = np.array(EPS1_SteerAngleSpd_next)
        EPS1_SteerAngleSpd = np.max(EPS1_SteerAngleSpd_next_nnp)

        lane_curve_list = []
        if found_index - 31 >= 0:
            lane_curve_list_fat = df_list[found_index - 31:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        else:
            lane_curve_list_fat = df_list[0:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        lane_curve = max(map(abs, lane_curve_list))
        logging.info("lane_curve: "+str(lane_curve))

        hour = start_time_str[11:13]
        data = {'AEB_Target_Estimated_Time_pre': [AEB_Target_Estimated_Time_pre],
                'AEB_Target_Estimated_Time_post': [AEB_Target_Estimated_Time_post],
                'AEB_Target_Longitudinal_Distance_pre': [AEB_Target_Longitudinal_Distance_pre],
                'AEB_Target_Longitudinal_Distance_post': [AEB_Target_Longitudinal_Distance_post],
                'AEB_Target_Cross_Range_pre': [AEB_Target_Cross_Range_pre],
                'AEB_Target_Cross_Range_post': [AEB_Target_Cross_Range_post],
                'AEB_Target_Longitudinal_Velocity_pre': [AEB_Target_Longitudinal_Velocity_pre],
                'AEB_Target_Longitudinal_Velocity_post': [AEB_Target_Longitudinal_Velocity_post],
                'AEB_Target_Lateral_Velocity_pre': [AEB_Target_Lateral_Velocity_pre],
                'AEB_Target_Lateral_Velocity_post': [AEB_Target_Lateral_Velocity_post],
                'IDB3_VehicleSpd_pre': [IDB3_VehicleSpd_pre],
                'IDB3_VehicleSpd_post': [IDB3_VehicleSpd_post],
                'ACU2_LongAccSensorValue_pre': [ACU2_LongAccSensorValue_pre],
                'ACU2_LongAccSensorValue_post': [ACU2_LongAccSensorValue_post],
                'ACU2_LatAccSensorValue_pre': [ACU2_LatAccSensorValue_pre],
                'ACU2_LatAccSensorValue_post': [ACU2_LatAccSensorValue_post],
                'ACU2_VehicleDynYawRate_pre': [ACU2_VehicleDynYawRate_pre],
                'ACU2_VehicleDynYawRate_post': [ACU2_VehicleDynYawRate_post],
                'AEB_Target_Estimated_Time_diff': [AEB_Target_Estimated_Time_diff],
                'AEB_Target_Longitudinal_Distance_diff': [AEB_Target_Longitudinal_Distance_diff],
                'AEB_Target_Cross_Range_diff': [AEB_Target_Cross_Range_diff],
                'AEB_Target_Longitudinal_Velocity_diff': [AEB_Target_Longitudinal_Velocity_diff],
                'AEB_Target_Lateral_Velocity_diff': [AEB_Target_Lateral_Velocity_diff],
                'IDB3_VehicleSpd_diff': [IDB3_VehicleSpd_diff],
                'ACU2_LongAccSensorValue_diff': [ACU2_LongAccSensorValue_diff],
                'ACU2_LatAccSensorValue_diff': [ACU2_LatAccSensorValue_diff],
                'ACU2_VehicleDynYawRate_diff': [ACU2_VehicleDynYawRate_diff],
                'IDB1_BrakePedalApplied': [IDB1_BrakePedalApplied],
                'EPS1_SteerAngleSpd': [EPS1_SteerAngleSpd],
                'lane_curve': [lane_curve],
                'hour': [hour]
                }
        df = pd.DataFrame(data)
    else:
        VLCCDHypotheses_Hypothesis_0_fTTC_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fTTC_last= [row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_last_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_last)
        AEB_Target_Estimated_Time_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fTTC_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fTTC_next =[row[3] for row in VLCCDHypotheses_Hypothesis_0_fTTC_next_list]
        VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fTTC_next)
        AEB_Target_Estimated_Time_post = np.mean(VLCCDHypotheses_Hypothesis_0_fTTC_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistX_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistX_last= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_last)
        AEB_Target_Longitudinal_Distance_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_last_nnp)


        VLCCDHypotheses_Hypothesis_0_fDistX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistX_next= [row[4] for row in VLCCDHypotheses_Hypothesis_0_fDistX_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistX_next)
        AEB_Target_Longitudinal_Distance_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fDistY_last = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_last_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_last)
        AEB_Target_Cross_Range_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fDistY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fDistY_next = [row[5] for row in VLCCDHypotheses_Hypothesis_0_fDistY_next_list]
        VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fDistY_next)
        AEB_Target_Cross_Range_post = np.mean(VLCCDHypotheses_Hypothesis_0_fDistY_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_last)
        AEB_Target_Longitudinal_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelX_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next = [row[6] for row in VLCCDHypotheses_Hypothesis_0_fVrelX_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelX_next)
        AEB_Target_Longitudinal_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelX_next_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_last_list = df_list[0:found_index - 1]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_last_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_last)
        AEB_Target_Lateral_Velocity_pre = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_last_nnp)

        VLCCDHypotheses_Hypothesis_0_fVrelY_next_list = df_list[found_index + 1:found_index + 11]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next = [row[7] for row in VLCCDHypotheses_Hypothesis_0_fVrelY_next_list]
        VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp = np.array(VLCCDHypotheses_Hypothesis_0_fVrelY_next)
        AEB_Target_Lateral_Velocity_post = np.mean(VLCCDHypotheses_Hypothesis_0_fVrelY_next_nnp)

        IDB3_VehicleSpd_last_list = df_list[0:found_index - 1]
        IDB3_VehicleSpd_last = [row[8] for row in IDB3_VehicleSpd_last_list]
        IDB3_VehicleSpd_last_nnp = np.array(IDB3_VehicleSpd_last)
        IDB3_VehicleSpd_pre = np.mean(IDB3_VehicleSpd_last_nnp)

        IDB3_VehicleSpd_last_next_list = df_list[found_index + 1:found_index + 11]
        IDB3_VehicleSpd_last_next = [row[8] for row in IDB3_VehicleSpd_last_next_list]
        IDB3_VehicleSpd_last_next_nnp = np.array(IDB3_VehicleSpd_last_next)
        IDB3_VehicleSpd_post = np.mean(IDB3_VehicleSpd_last_next_nnp)

        ACU2_LongAccSensorValue_last_list = df_list[0:found_index - 1]
        ACU2_LongAccSensorValue_last = [row[9] for row in ACU2_LongAccSensorValue_last_list]
        ACU2_LongAccSensorValue_last_nnp = np.array(ACU2_LongAccSensorValue_last)
        ACU2_LongAccSensorValue_pre = np.mean(ACU2_LongAccSensorValue_last_nnp)

        ACU2_LongAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LongAccSensorValue_next = [row[9] for row in ACU2_LongAccSensorValue_next_list]
        ACU2_LongAccSensorValue_next_nnp = np.array(ACU2_LongAccSensorValue_next)
        ACU2_LongAccSensorValue_post = np.mean(ACU2_LongAccSensorValue_next_nnp)

        ACU2_LatAccSensorValue_last_list = df_list[0:found_index - 1]
        ACU2_LatAccSensorValue_last = [row[10] for row in ACU2_LatAccSensorValue_last_list]
        ACU2_LatAccSensorValue_last_nnp = np.array(ACU2_LatAccSensorValue_last)
        ACU2_LatAccSensorValue_pre = np.mean(ACU2_LatAccSensorValue_last_nnp)

        ACU2_LatAccSensorValue_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_LatAccSensorValue_next = [row[10] for row in ACU2_LatAccSensorValue_next_list]
        ACU2_LatAccSensorValue_next_nnp = np.array(ACU2_LatAccSensorValue_next)
        ACU2_LatAccSensorValue_post = np.mean(ACU2_LatAccSensorValue_next_nnp)

        ACU2_VehicleDynYawRate_last_list = df_list[0:found_index - 1]
        ACU2_VehicleDynYawRate_last = [row[11] for row in ACU2_VehicleDynYawRate_last_list]
        ACU2_VehicleDynYawRate_last_nnp = np.array(ACU2_VehicleDynYawRate_last)
        ACU2_VehicleDynYawRate_pre = np.mean(ACU2_VehicleDynYawRate_last_nnp)

        ACU2_VehicleDynYawRate_next_list = df_list[found_index + 1:found_index + 11]
        ACU2_VehicleDynYawRate_next = [row[11] for row in ACU2_VehicleDynYawRate_next_list]
        ACU2_VehicleDynYawRate_next_nnp = np.array(ACU2_VehicleDynYawRate_next)
        ACU2_VehicleDynYawRate_post = np.mean(ACU2_VehicleDynYawRate_next_nnp)

        AEB_Target_Estimated_Time_diff = AEB_Target_Estimated_Time_post - AEB_Target_Estimated_Time_pre
        AEB_Target_Longitudinal_Distance_diff = AEB_Target_Longitudinal_Distance_post - AEB_Target_Longitudinal_Distance_pre
        AEB_Target_Cross_Range_diff = AEB_Target_Cross_Range_post - AEB_Target_Cross_Range_pre
        AEB_Target_Longitudinal_Velocity_diff = AEB_Target_Longitudinal_Velocity_post - AEB_Target_Longitudinal_Velocity_pre
        AEB_Target_Lateral_Velocity_diff = AEB_Target_Lateral_Velocity_post - AEB_Target_Lateral_Velocity_pre
        IDB3_VehicleSpd_diff = IDB3_VehicleSpd_post - IDB3_VehicleSpd_pre
        ACU2_LongAccSensorValue_diff = ACU2_LongAccSensorValue_post - ACU2_LongAccSensorValue_pre
        ACU2_LatAccSensorValue_diff = ACU2_LatAccSensorValue_post - ACU2_LatAccSensorValue_pre
        ACU2_VehicleDynYawRate_diff = ACU2_VehicleDynYawRate_post - ACU2_VehicleDynYawRate_pre

        IDB1_BrakePedalApplied_next_list = df_list[found_index + 1:found_index + 11]
        IDB1_BrakePedalApplied_next = [row[12] for row in IDB1_BrakePedalApplied_next_list]
        IDB1_BrakePedalApplied_next_nnp = np.array(IDB1_BrakePedalApplied_next)
        IDB1_BrakePedalApplied = np.mean(IDB1_BrakePedalApplied_next_nnp)

        EPS1_SteerAngleSpd_next_list = df_list[found_index + 1:found_index + 11]
        EPS1_SteerAngleSpd_next = [row[13] for row in EPS1_SteerAngleSpd_next_list]
        EPS1_SteerAngleSpd_next_nnp = np.array(EPS1_SteerAngleSpd_next)
        EPS1_SteerAngleSpd = np.max(EPS1_SteerAngleSpd_next_nnp)

        if found_index - 31 >= 0:
            lane_curve_list_fat = df_list[found_index - 31:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        else:
            lane_curve_list_fat = df_list[0:found_index - 1]
            lane_curve_list = [row[14] for row in lane_curve_list_fat]
        lane_curve = max(map(abs, lane_curve_list))
        logging.info("lane_curve: "+str(lane_curve))

        hour = start_time_str[11:13]
        data = {'AEB_Target_Estimated_Time_pre': [AEB_Target_Estimated_Time_pre],
                'AEB_Target_Estimated_Time_post': [AEB_Target_Estimated_Time_post],
                'AEB_Target_Longitudinal_Distance_pre': [AEB_Target_Longitudinal_Distance_pre],
                'AEB_Target_Longitudinal_Distance_post': [AEB_Target_Longitudinal_Distance_post],
                'AEB_Target_Cross_Range_pre': [AEB_Target_Cross_Range_pre],
                'AEB_Target_Cross_Range_post': [AEB_Target_Cross_Range_post],
                'AEB_Target_Longitudinal_Velocity_pre': [AEB_Target_Longitudinal_Velocity_pre],
                'AEB_Target_Longitudinal_Velocity_post': [AEB_Target_Longitudinal_Velocity_post],
                'AEB_Target_Lateral_Velocity_pre': [AEB_Target_Lateral_Velocity_pre],
                'AEB_Target_Lateral_Velocity_post': [AEB_Target_Lateral_Velocity_post],
                'IDB3_VehicleSpd_pre': [IDB3_VehicleSpd_pre],
                'IDB3_VehicleSpd_post': [IDB3_VehicleSpd_post],
                'ACU2_LongAccSensorValue_pre': [ACU2_LongAccSensorValue_pre],
                'ACU2_LongAccSensorValue_post': [ACU2_LongAccSensorValue_post],
                'ACU2_LatAccSensorValue_pre': [ACU2_LatAccSensorValue_pre],
                'ACU2_LatAccSensorValue_post': [ACU2_LatAccSensorValue_post],
                'ACU2_VehicleDynYawRate_pre': [ACU2_VehicleDynYawRate_pre],
                'ACU2_VehicleDynYawRate_post': [ACU2_VehicleDynYawRate_post],
                'AEB_Target_Estimated_Time_diff': [AEB_Target_Estimated_Time_diff],
                'AEB_Target_Longitudinal_Distance_diff': [AEB_Target_Longitudinal_Distance_diff],
                'AEB_Target_Cross_Range_diff': [AEB_Target_Cross_Range_diff],
                'AEB_Target_Longitudinal_Velocity_diff': [AEB_Target_Longitudinal_Velocity_diff],
                'AEB_Target_Lateral_Velocity_diff': [AEB_Target_Lateral_Velocity_diff],
                'IDB3_VehicleSpd_diff': [IDB3_VehicleSpd_diff],
                'ACU2_LongAccSensorValue_diff': [ACU2_LongAccSensorValue_diff],
                'ACU2_LatAccSensorValue_diff': [ACU2_LatAccSensorValue_diff],
                'ACU2_VehicleDynYawRate_diff': [ACU2_VehicleDynYawRate_diff],
                'IDB1_BrakePedalApplied': [IDB1_BrakePedalApplied],
                'EPS1_SteerAngleSpd': [EPS1_SteerAngleSpd],
                'lane_curve': [lane_curve],
                'hour': [hour]
                }
        df = pd.DataFrame(data)
    return df
# 文件上传：
def convert_to_binary_with_length(number, desired_length):
    # 转成二进制
    binary_representation = bin(number)[2:]

    # 在二进制字符串前面补零，使其总长度为设定的长度
    binary_representation = binary_representation.zfill(desired_length)

    # 返回结果
    return binary_representation
def get_binary_with(SuppressReason):
    # 设定希望的二进制长度
    desired_length = 16
    # 获取二进制表示的位数
    num_bits = SuppressReason.bit_length()
    # 动态调整长度并获取二进制表示
    binary_representation = convert_to_binary_with_length(SuppressReason, max(num_bits, desired_length))
    return binary_representation
def get_binary_with_27(SuppressReason):
    # 设定希望的二进制长度
    desired_length = 27
    # 获取二进制表示的位数
    num_bits = SuppressReason.bit_length()
    # 动态调整长度并获取二进制表示
    binary_representation = convert_to_binary_with_length(SuppressReason, max(num_bits, desired_length))
    return binary_representation
def get_can_out_100ms_list(df_can_100ms_nnp_active_list,nsecs,start_time):
    subset_list = [item for item in df_can_100ms_nnp_active_list if item[0] == start_time]
    # 找到最接近目标值的行数据
    if not subset_list:
        return None
    closest_data = min(subset_list, key=lambda x: abs(x[2] - nsecs))

    # 打印结果
    return  closest_data
def get_can_out_20ms_list(df_can_20ms_list,nsecs,start_time):
    subset_list = [item for item in df_can_20ms_list if item[0] == start_time]
    # 找到最接近目标值的行数据
    if not subset_list:
        return None
    closest_data = min(subset_list, key=lambda x: abs(x[2] - nsecs))

    # 打印结果
    return  closest_data
def get_can_in_list(df_can_100ms_nnp_active_list,nsecs,start_time):
    subset_list = [item for item in df_can_100ms_nnp_active_list if item[0] == start_time]
    # 找到最接近目标值的行数据
    if not subset_list:
        return None
    closest_data = min(subset_list, key=lambda x: abs(x[2] - nsecs))

    # 打印结果
    return  closest_data
def uploadjson(bucket_name,object_key,jsonstr):
    try:
        client = tos.TosClientV2(ak, sk, endpoint, region)
        # 若在上传对象时设置文件存储类型（x-tos-storage-class）和访问权限 (x-tos-acl), 请在 put_object中设置相关参数
        # 用户在上传对象时，可以自定义元数据，以便对对象进行自定义管理
        # result = client.put_object(bucket_name, object_key, content=content, acl=tos.ACLType.ACL_Private, storage_class=tos.StorageClassType.Storage_Class_Standard, meta={'name': '张三', 'age': '20'})
        result = client.put_object(bucket_name, object_key, content=jsonstr)
        # HTTP状态码
        print('http status code:{}'.format(result.status_code))
        # 请求ID。请求ID是本次请求的唯一标识，建议在日志中添加此参数
        print('request_id: {}'.format(result.request_id))
        # hash_crc64_ecma 表示该对象的64位CRC值, 可用于验证上传对象的完整性
        print('crc64: {}'.format(result.hash_crc64_ecma))
    except tos.exceptions.TosClientError as e:
        # 操作失败，捕获客户端异常，一般情况为非法请求参数或网络异常
        print('fail with client error, message:{}, cause: {}'.format(e.message, e.cause))
    except tos.exceptions.TosServerError as e:
        # 操作失败，捕获服务端异常，可从返回信息中获取详细错误信息
        print('fail with server error, code: {}'.format(e.code))
        # request id 可定位具体问题，强烈建议日志中保存
        print('error with request id: {}'.format(e.request_id))
        print('error with message: {}'.format(e.message))
        print('error with http code: {}'.format(e.status_code))
        print('error with ec: {}'.format(e.ec))
        print('error with request url: {}'.format(e.request_url))
    except Exception as e:
        print('fail with unknown error: {}'.format(e))
def get_timestamp(time_string):
    # 转换为时间元组
    time_tuple = time.strptime(time_string, "%Y-%m-%d %H:%M:%S")
    # 转换为时间戳
    timestamp = str(int(time.mktime(time_tuple)*1000))
    return timestamp
def add_to_mysql(json_str):
    # 配置数据库连接信息
    db_config = {
        'host': 'mysql-d8beb8b0655b-public.rds.volces.com',
        'user': 'user01',
        'password': 'password123!#',
        'database': 'bi_test'
    }
    # 创建数据库连接
    conn = mysql.connector.connect(**db_config)
    cursor = conn.cursor()

    # 假设你有一个名为 'your_table' 的表，包含 'column1', 'column2', 'column3' 等字段
    table_name = 'trigger_sc_ep40_tda4'

    # 假设你有一个数据字典，包含要插入的数据
    data_to_insert = json.loads(json_str)

    # 构建 SQL 插入语句
    columns = ', '.join(data_to_insert.keys())
    values = ', '.join(['%s'] * len(data_to_insert))
    sql_insert = f"replace into {table_name} ({columns}) VALUES ({values})"

    # 执行插入操作
    cursor.execute(sql_insert, list(data_to_insert.values()))

    # 提交更改
    conn.commit()
def get_label_nnp_active_can_100ms(path_st_100ms,path_st_can_out,path_st_can_in,path_st_20ms, vechicle_id,daystr,hourstr, bagid, uuids, file_type):
    try:
        df_can_100ms_nnp_active = pd.read_pickle(path_st_100ms)
    except Exception as e:
        print('data report read error, ', str(e))

    try:
        df_can_out_nnp_active = pd.read_pickle(path_st_can_out)
    except Exception as e:
        print('data report read error, ', str(e))

    try:
        df_can_in_nnp_active = pd.read_pickle(path_st_can_in)
    except Exception as e:
        print('data report read error, ', str(e))

    try:
        df_can_20ms_nnp_active = pd.read_pickle(path_st_20ms)
    except Exception as e:
        print('data report read error, ', str(e))

    df_can_out_nnp_active_list = df_can_out_nnp_active[
        ['start_time_str','path','ADCS8_NNPSysState','ADCS12_NNP_State_Reminder','ADCS12_P2N_State_Reminder','nsecs','ADCS12_longitudDisableInfo','ADCS12_NPilotSysInfo','NNP_out_reserved8']].values.tolist()

    df_can_100ms_nnp_active_list = df_can_100ms_nnp_active[
        ['start_time_str', 'path', 'nsecs', 'ICU2_Odometer', 'IDB3_VehicleSpd', 'ACU2_LongAccSensorValue',
         'ACU2_LatAccSensorValue', 'ACU2_VehicleDynYawRate', 'EPS1_SteerAngleSpd', 'EPS1_TorsionBarTorque',
         'CS1_GearPositionReqSt', 'IDB1_BrakePedalApplied', 'IDB1_BrakePedalAppliedV','ADCS2_AEBPartialBrake','ADCS2_AEBFullBrake',
         'ADCS8_ACCState','CamLaneData_CourseInfo_1_CourseInfoSegNear_f_Length','CamLaneData_CourseInfo_2_CourseInfoSegNear_f_Length','CamLaneData_LaneMarkerInfo_1_f_MarkerDist','CamLaneData_LaneMarkerInfo_2_f_MarkerDist',
         'g_LCF_TJASA_Output_TJASTM_SysStateTJA_nu','g_LCFSEN_proDebugs_sTJASADebug_TJALKA_StrongReady_bool','g_LCFSEN_proDebugs_sTJASADebug_TJALKA_WeakReady_bool','g_LCFSEN_proDebugs_sTJASADebug_TJALKA_LaneCenterInvalid_btf'

         ]].values.tolist()
    df_can_in_nnp_active_list=df_can_in_nnp_active[
        ['start_time_str','path','nsecs','IDB7_HDCAtive','Region_A_SwError']].values.tolist()

    df_can_20ms_nnp_active_list=df_can_20ms_nnp_active[
        ['start_time_str','path','nsecs','SuppressReason']].values.tolist()

    #触发时状态： df_can_100ms_nnp_active
    dict_list=[]
    scid_dict=get_scid_time(df_can_out_nnp_active, df_can_100ms_nnp_active)

    ADCS8_NNPSysState_last=df_can_out_nnp_active_list[0][2]
    ADCS12_NNP_State_Reminder_last=df_can_out_nnp_active_list[0][3]
    ADCS12_P2N_State_Reminder_last=df_can_out_nnp_active_list[0][4]
    ADCS12_longitudDisableInfo_last=df_can_out_nnp_active_list[0][6]
    for row in df_can_out_nnp_active_list:
        start_time_str=row[0]
        path = row[1]
        ADCS8_NNPSysState = row[2]
        ADCS12_NNP_State_Reminder = row[3]
        ADCS12_P2N_State_Reminder=row[4]
        nsecs = row[5]
        ADCS12_longitudDisableInfo= row[6]
        ADCS12_NPilotSysInfo = row[7]
        NNP_out_reserved8 = int(row[8])

        if ADCS8_NNPSysState_last==1 and ADCS8_NNPSysState==2:
            level1 = "NNP激活"
            level2 = "NNP激活成功"
            level3 = ""
            dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
            data_list = get_dict_list(dict)
            dict_list.append(data_list)

        if (ADCS12_NNP_State_Reminder_last!=7 and ADCS12_NNP_State_Reminder==7) or (ADCS12_P2N_State_Reminder_last!=7 and ADCS12_P2N_State_Reminder==7):
            level1 = "NNP激活"
            level2 = "NNP激活失败"
            level3 = ""
            dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
            data_list = get_dict_list(dict)
            dict_list.append(data_list)

        if (ADCS12_NNP_State_Reminder_last != 7 and ADCS12_NNP_State_Reminder == 7) or (ADCS12_P2N_State_Reminder_last != 7 and ADCS12_P2N_State_Reminder == 7):
            binary_representation = get_binary_with(NNP_out_reserved8)

            list_100ms = get_can_out_100ms_list(df_can_100ms_nnp_active_list, nsecs, start_time_str)
            if list_100ms is not None and len(list_100ms) > 0:
                IDB1_BrakePedalApplied = list_100ms[11]
                IDB1_BrakePedalAppliedV = list_100ms[12]
                ADCS2_AEBPartialBrake = list_100ms[13]
                ADCS2_AEBFullBrake = list_100ms[14]

                if IDB1_BrakePedalApplied == 1 and IDB1_BrakePedalAppliedV == 0:
                    level1 = "NNP激活"
                    level2 = "NNP激活失败"
                    level3 = "原因：刹车踏板踩下或刹车踏板信号无效"

                    dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)
                if (ADCS2_AEBPartialBrake == 1 or ADCS2_AEBFullBrake == 1):
                    level1 = "NNP激活"
                    level2 = "NNP激活失败"
                    level3 = "原因：AEB介入"
                    dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

            list_can_in = get_can_in_list(df_can_in_nnp_active_list, nsecs, start_time_str)
            if list_can_in is not None and len(list_can_in) > 0:
                IDB7_HDCAtive = list_can_in[3]
                Region_A_SwError = list_can_in[4]

                if IDB7_HDCAtive == 1:
                    level1 = "NNP激活"
                    level2 = "NNP激活失败"
                    level3 = "原因：HDC激活"

                    dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)

                if Region_A_SwError == 1:
                    level1 = "NNP激活"
                    level2 = "NNP激活失败"
                    level3 = "原因：左方控ACC按键无效"
                    dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                    data_list = get_dict_list(dict)
                    dict_list.append(data_list)



            if ADCS12_longitudDisableInfo in [4,5,6] or ADCS12_NPilotSysInfo in [8,9,10]:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：四门两盖任一处于开启状态"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if ADCS12_longitudDisableInfo==1 or ADCS12_NPilotSysInfo==4:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：速度不满足"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if (ADCS12_longitudDisableInfo_last!=7 and ADCS12_longitudDisableInfo==7) or (ADCS12_NPilotSysInfo==11):
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：EPB处于激活状态"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)


            if ADCS8_NNPSysState==6:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：系统故障"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)


            # 根据每个位的值设置相应的变量
            logging.info("NNP_out_reserved8: "+str(NNP_out_reserved8))
            Bite0 = int(binary_representation[-1])
            Bite1 = int(binary_representation[-2])
            Bite2 = int(binary_representation[-3])
            Bite3 = int(binary_representation[-4])
            Bite4 = int(binary_representation[-5])
            Bite5 = int(binary_representation[-6])
            Bite6 = int(binary_representation[-7])
            Bite7 = int(binary_representation[-8])
            Bite8 = int(binary_representation[-9])
            Bite9 = int(binary_representation[-10])
            Bite10 = int(binary_representation[-11])
            Bite11 = int(binary_representation[-12])
            Bite12 = int(binary_representation[-13])
            Bite13 = int(binary_representation[-14])
            Bite14 = int(binary_representation[-15])
            Bite15 = int(binary_representation[-16])
            if Bite0:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Pilot function quit"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

                list_100ms = get_can_out_100ms_list(df_can_100ms_nnp_active_list, nsecs,start_time_str)
                if list_100ms is not None and len(list_100ms) > 0:
                    ADCS8_ACCState = list_100ms[15]
                    CamLaneData_CourseInfo_1_CourseInfoSegNear_f_Length = list_100ms[16]
                    CamLaneData_CourseInfo_2_CourseInfoSegNear_f_Length = list_100ms[17]
                    CamLaneData_LaneMarkerInfo_1_f_MarkerDist = list_100ms[18]
                    CamLaneData_LaneMarkerInfo_2_f_MarkerDist = list_100ms[19]
                    g_LCF_TJASA_Output_TJASTM_SysStateTJA_nu = list_100ms[20]
                    g_LCFSEN_proDebugs_sTJASADebug_TJALKA_StrongReady_bool = list_100ms[21]
                    g_LCFSEN_proDebugs_sTJASADebug_TJALKA_WeakReady_bool = list_100ms[22]

                    if ADCS8_ACCState not in [1, 2]:
                        level1 = "NNP激活"
                        level2 = "NNP激活失败"
                        level3 = "原因：不满足ACC激活条件"
                        dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                        data_list = get_dict_list(dict)
                        dict_list.append(data_list)

                    if CamLaneData_CourseInfo_1_CourseInfoSegNear_f_Length < 15 or CamLaneData_CourseInfo_2_CourseInfoSegNear_f_Length < 15:
                        logging.info("start_time_str: "+start_time_str)
                        logging.info("start_time_str: " + start_time_str)
                        level1 = "NNP激活"
                        level2 = "NNP激活失败"
                        level3 = "原因：车道线长度不满足"
                        dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                        data_list = get_dict_list(dict)
                        dict_list.append(data_list)
                    if abs(
                            CamLaneData_LaneMarkerInfo_1_f_MarkerDist - CamLaneData_LaneMarkerInfo_2_f_MarkerDist) < 2.6 or abs(
                            CamLaneData_LaneMarkerInfo_1_f_MarkerDist - CamLaneData_LaneMarkerInfo_2_f_MarkerDist) > 5.2:
                        level1 = "NNP激活"
                        level2 = "NNP激活失败"
                        level3 = "原因：车道线宽度不满足"
                        dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                        data_list = get_dict_list(dict)
                        dict_list.append(data_list)
                    if g_LCF_TJASA_Output_TJASTM_SysStateTJA_nu == 7:
                        level1 = "NNP激活"
                        level2 = "NNP激活失败"
                        level3 = "原因：PILOT关闭"
                        dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                        data_list = get_dict_list(dict)
                        dict_list.append(data_list)
                    if g_LCF_TJASA_Output_TJASTM_SysStateTJA_nu == 1 and (
                            g_LCFSEN_proDebugs_sTJASADebug_TJALKA_StrongReady_bool == 0 or g_LCFSEN_proDebugs_sTJASADebug_TJALKA_WeakReady_bool == 0):
                        list_100ms2 = get_can_out_100ms_list(df_can_100ms_nnp_active_list, nsecs, start_time_str)
                        if list_100ms2 is not None and len(list_100ms2) > 0:
                            g_LCFSEN_proDebugs_sTJASADebug_TJALKA_LaneCenterInvalid_btf = list_100ms2[23]
                            binary_representation1 = get_binary_with(
                                g_LCFSEN_proDebugs_sTJASADebug_TJALKA_LaneCenterInvalid_btf)
                            # 根据每个位的值设置相应的变量
                            bit0 = int(binary_representation1[-1])
                            bit1 = int(binary_representation1[-2])
                            bit2 = int(binary_representation1[-3])
                            bit3 = int(binary_representation1[-4])
                            bit4 = int(binary_representation1[-5])
                            bit5 = int(binary_representation1[-6])
                            bit6 = int(binary_representation1[-7])
                            bit7 = int(binary_representation1[-8])
                            bit8 = int(binary_representation1[-9])
                            bit9 = int(binary_representation1[-10])
                            bit10 = int(binary_representation1[-11])
                            bit11 = int(binary_representation1[-12])
                            bit12 = int(binary_representation1[-13])
                            bit13 = int(binary_representation1[-14])
                            bit14 = int(binary_representation1[-15])
                            bit15 = int(binary_representation1[-16])

                            if bit0:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车道线无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)
                            if bit1:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：超速"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit2:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：距离车道边界过近"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit3:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车道宽度不满足"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit4:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车道线曲率不满足"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit5:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：信号灯激活"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit6:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：检测到在施工现场(默认是不在的)"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit7:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：无法居中"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit8:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：strongready条件不满足"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit9:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：仅有跟车模式(这个模式已关闭)"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit10:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：检测到在变道"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit11:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车道线长度不满足"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit12:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车道线不在检测范围内"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit13:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：Blocking TimeOn（延迟时间较长）"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit14:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：主动取消"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if bit15:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：被动取消"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                    if ADCS8_ACCState not in [1, 2]:
                        list_20ms = get_can_out_20ms_list(df_can_20ms_nnp_active_list, nsecs, start_time_str)
                        if list_20ms is not None and len(list_20ms) > 0:
                            SuppressReason = list_20ms[3]
                            SuppressReason_arr = get_binary_with_27(SuppressReason)
                            # 根据每个位的值设置相应的变量
                            s_Bite0 = int(SuppressReason_arr[-1])
                            s_Bite1 = int(SuppressReason_arr[-2])
                            s_Bite2 = int(SuppressReason_arr[-3])
                            s_Bite3 = int(SuppressReason_arr[-4])
                            s_Bite4 = int(SuppressReason_arr[-5])
                            s_Bite5 = int(SuppressReason_arr[-6])
                            s_Bite6 = int(SuppressReason_arr[-7])
                            s_Bite7 = int(SuppressReason_arr[-8])
                            s_Bite8 = int(SuppressReason_arr[-9])
                            s_Bite9 = int(SuppressReason_arr[-10])
                            s_Bite10 = int(SuppressReason_arr[-11])
                            s_Bite11 = int(SuppressReason_arr[-12])
                            s_Bite12 = int(SuppressReason_arr[-13])
                            s_Bite13 = int(SuppressReason_arr[-14])
                            s_Bite14 = int(SuppressReason_arr[-15])
                            s_Bite15 = int(SuppressReason_arr[-16])
                            s_Bite16 = int(SuppressReason_arr[-17])
                            s_Bite17 = int(SuppressReason_arr[-18])
                            s_Bite18 = int(SuppressReason_arr[-19])
                            s_Bite19 = int(SuppressReason_arr[-20])
                            s_Bite20 = int(SuppressReason_arr[-21])
                            s_Bite21 = int(SuppressReason_arr[-22])
                            s_Bite22 = int(SuppressReason_arr[-23])
                            s_Bite23 = int(SuppressReason_arr[-24])
                            s_Bite24 = int(SuppressReason_arr[-25])
                            s_Bite25 = int(SuppressReason_arr[-26])
                            s_Bite26 = int(SuppressReason_arr[-27])

                            if s_Bite0:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：ACCreset"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)
                            if s_Bite1:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：诊断出故障"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)
                            if s_Bite2:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：无目标时车速低于 15"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite3:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：ABS,ESC,TCS,ARP 激活"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite4:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：解安全带"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite5:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车速过高"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite6:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：曲率过大"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite7:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：加速度过大"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite8:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：四门两盖"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite9:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：踩制动"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite10:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：VCU ACC not ready"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite11:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：ACC not enable IDB5_ACC _Enable"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite12:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：EPB not allow"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite13:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：Act gear 不在驱动档或无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite14:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：后溜"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite15:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：AEB 或相关激活"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite16:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：IDB7_DynParkBrkByIDBActive"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite17:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：HDC 激活，TCS 不可用"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite18:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：泊车系统"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite19:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：ACC_ReqLim==0x03 或制动盘过热或 ABS EBD ESC TCS fail"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite20:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：油门无效或 standstill 无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite21:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：横向加速度纵向加速度 yawrate 无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite22:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：车轮方向无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite23:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：转向角信号无效"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite24:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：故障诊断的抑制信号"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite25:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：融合目标时间戳不变导致故障"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)

                            if s_Bite26:
                                level1 = "NNP激活"
                                level2 = "NNP激活失败"
                                level3 = "原因：融合线时间戳不变导致故障"
                                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2,
                                                level3)
                                data_list = get_dict_list(dict)
                                dict_list.append(data_list)





            if Bite1:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：NNP is CoolingDown, wait for resume"

                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)




            if Bite2:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：HDmap EgoLane Quality is not valid"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite3:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：HDmap EgoLane Width not large than min || Curve not less than"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if Bite4:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：HDmap not valid road can not drive"

                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite5:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：HDmap EgoLane Heading not small than max"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite6:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Position info invalid more than 1 secs"

                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite7:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Navigation info quit || invalid"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite8:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：APSM quit to S4"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite9:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：ACC invalid"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite10:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Brake pedal pressed Hazrd light on"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
            if Bite11:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Manual Torque Override"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if Bite12:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：Vehicle Velocity > 140kph"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if Bite13:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：FCB ERROR"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if Bite14:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：RCA ERROR"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)

            if Bite15:
                level1 = "NNP激活"
                level2 = "NNP激活失败"
                level3 = "原因：FCA ERROR"
                dict = get_dict(vechicle_id, start_time_str, bagid, path, scid_dict, level1, level2, level3)
                data_list = get_dict_list(dict)
                dict_list.append(data_list)
        print("记录上一条记录。。。")
        ADCS8_NNPSysState_last=ADCS8_NNPSysState
        ADCS12_NNP_State_Reminder_last =ADCS12_NNP_State_Reminder
        ADCS12_P2N_State_Reminder_last =ADCS12_P2N_State_Reminder
        ADCS12_longitudDisableInfo_last=ADCS12_longitudDisableInfo
    add_to_bytehouse(dict_list)
def get_model_nnp_active_canout(df_can_100ms_save_path,df_can_canout_save_path, vechicle_id, daystr, hourstr, bagid, uuids, file_type, dtc,sc):
    try:
        df_nnp_can_100ms = pd.read_pickle(df_can_100ms_save_path)
        print(df_nnp_can_100ms.columns)
    except Exception as e:
        print('data report read error, ', str(e))
    df_nnp_can100ms_list= df_nnp_can_100ms[
        ['start_time_str','path','nsecs','VLCCDHypotheses_Hypothesis_0_fTTC','VLCCDHypotheses_Hypothesis_0_fDistX','VLCCDHypotheses_Hypothesis_0_fDistY',
         'VLCCDHypotheses_Hypothesis_0_fVrelX','VLCCDHypotheses_Hypothesis_0_fVrelY','IDB3_VehicleSpd','ACU2_LongAccSensorValue','ACU2_LatAccSensorValue',
         'ACU2_VehicleDynYawRate','IDB1_BrakePedalApplied','EPS1_SteerAngleSpd','CamLaneData_CourseInfo_1_CourseInfoSegNear_f_C0',
         'ICU2_Odometer','EPS1_TorsionBarTorque','CS1_GearPositionReqSt'
         ]].values.tolist()

    try:
        df_nnp_can_out = pd.read_pickle(df_can_canout_save_path)
        print(df_nnp_can_out.columns)
    except Exception as e:
        print('data report read error, ', str(e))
    df_nnp_canout_list= df_nnp_can_out[
        ['start_time_str','path','nsecs','ADCS8_NNPSysState','ADCS12_NNP_State_Reminder','ADCS12_P2N_State_Reminder'
         ]].values.tolist()


    found_index = -9999
    start_time_str=""
    found_nsecs=0

    # 遍历列表
    ADCS8_NNPSysState_last=df_nnp_canout_list[0][3]
    for index, element in enumerate(df_nnp_canout_list):
        start_time_str=element[0]
        path = element[1]
        nsecs = element[2]
        ADCS8_NNPSysState = element[3]
        ADCS12_NNP_State_Reminder = element[4]
        ADCS12_P2N_State_Reminder = element[5]
        if (ADCS8_NNPSysState_last==1 and ADCS8_NNPSysState==2) or (ADCS12_NNP_State_Reminder==2) or (ADCS12_NNP_State_Reminder==7) or (ADCS12_P2N_State_Reminder==7):
            found_index = index
            found_nsecs=nsecs
            break  # 找到第一个符合条件的元素就跳出循环
        ADCS8_NNPSysState_last=ADCS8_NNPSysState
    logging.info("found_index: "+str(found_index))
    logging.info("found_nsecs: " + str(found_nsecs))

    list_data,index_100ms=get_can_100ms_list(df_nnp_can100ms_list, found_nsecs)
    df=get_model_feature(index_100ms, df_nnp_can100ms_list, start_time_str)
    df_std = sc.transform(df)
    y_pred = dtc.predict(df_std)
    logging.info("预测结果： " + str(y_pred))

    ICU2_Odometer =list_data[15]
    IDB3_VehicleSpd = list_data[8]
    ACU2_LongAccSensorValue =list_data[9]
    ACU2_LatAccSensorValue =list_data[10]
    ACU2_VehicleDynYawRate = list_data[11]
    EPS1_SteerAngleSpd = list_data[13]
    lane_curvature= list_data[14]
    EPS1_TorsionBarTorque = list_data[16]
    CS1_GearPositionReqSt =list_data[17]
    # 输出值为2代表已碰撞，1代表危险但未碰撞，0代表不危险
    if y_pred[0] == 2:
        level1 = "已碰撞"
    elif y_pred[0] == 1:
        level1 = "危险但未碰撞"
    elif y_pred[0] == 0:
        level1 = "不危险"
    dict = {}
    dict["vehicle_id"] = vechicle_id
    dict["start_time_str"] = start_time_str
    dict["scid"] = bagid
    dict["path"] = path
    level2 = ""
    level3 = ""
    dict["level1"] = level1
    dict["level2"] = level2
    dict["level3"] = level3
    day = start_time_str[0:4] + start_time_str[5:7] + start_time_str[8:10]
    month = start_time_str[0:4] + start_time_str[5:7]
    dict["day"] = day
    dict["month"] = month
    dict["scid_start_time_str"] =start_time_str
    dict["icu2_odometer"] = ICU2_Odometer
    dict["idb3_vehiclespd"] = IDB3_VehicleSpd
    dict["acu2_longaccsensorvalue"] =ACU2_LongAccSensorValue
    dict["acu2_lataccsensorvalue"] = ACU2_LatAccSensorValue
    dict["acu2_vehicledynyawrate"] = ACU2_VehicleDynYawRate
    dict["eps1_steeranglespd"] = EPS1_SteerAngleSpd
    dict["lane_curvature"] = lane_curvature
    dict["eps1_torsionbartorque"] = EPS1_TorsionBarTorque
    dict["cs1_gearpositionreqst"] =CS1_GearPositionReqSt

    uid_string = vechicle_id + start_time_str + bagid + level1 + level2 + level3
    uid = str(uuid.uuid3(uuid.NAMESPACE_DNS, uid_string))
    dict["uid"] = uid

    json_string = json.dumps(dict, ensure_ascii=False, indent=None)
    add_to_bytehouse_dict(dict)


